Created
April 28, 2013 20:05
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Test case where MplusAutomation does not read the warning.
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| tf<-tempfile(fileext=".out") | |
| cat('Mplus VERSION 6.11 (Mac) | |
| MUTHEN & MUTHEN | |
| 04/28/2013 10:56 PM | |
| INPUT INSTRUCTIONS | |
| TITLE: Your title goes here | |
| DATA: FILE = "/tmp/file16b7d2a90effc/mplusdata.dat"; | |
| VARIABLE: | |
| NAMES = i1 i2 i3 i4 i5 i6 i7 i8 i9 i10 i11 i12 i13 i14 i15 i16 i17 i18; | |
| ANALYSIS: | |
| MODEL = NOMEANSTRUCTURE; | |
| INFORMATION = EXPECTED; | |
| MODEL: | |
| C1 BY i1 i2 i3; | |
| C2 BY i4 i5 i6; | |
| C3 BY i7 i8 i9; | |
| C4 BY i10 i11 i12; | |
| C5 BY i13 i14 i15; | |
| C6 BY i16 i17 i18; | |
| C2 ON C1; | |
| C3 ON C1 C2; | |
| C4 ON C1 C3; | |
| C5 ON C1 C3; | |
| C6 ON C4; | |
| OUTPUT: STANDARDIZED (STDYX); | |
| INPUT READING TERMINATED NORMALLY | |
| Your title goes here | |
| SUMMARY OF ANALYSIS | |
| Number of groups 1 | |
| Number of observations 100 | |
| Number of dependent variables 18 | |
| Number of independent variables 0 | |
| Number of continuous latent variables 6 | |
| Observed dependent variables | |
| Continuous | |
| I1 I2 I3 I4 I5 I6 | |
| I7 I8 I9 I10 I11 I12 | |
| I13 I14 I15 I16 I17 I18 | |
| Continuous latent variables | |
| C1 C2 C3 C4 C5 C6 | |
| Estimator ML | |
| Information matrix EXPECTED | |
| Maximum number of iterations 1000 | |
| Convergence criterion 0.500D-04 | |
| Maximum number of steepest descent iterations 20 | |
| Input data file(s) | |
| /tmp/file16b7d2a90effc/mplusdata.dat | |
| Input data format FREE | |
| THE MODEL ESTIMATION TERMINATED NORMALLY | |
| WARNING: THE LATENT VARIABLE COVARIANCE MATRIX (PSI) IS NOT POSITIVE | |
| DEFINITE. THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR A | |
| LATENT VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO LATENT | |
| VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO LATENT VARIABLES. | |
| CHECK THE TECH4 OUTPUT FOR MORE INFORMATION. | |
| PROBLEM INVOLVING VARIABLE C5. | |
| MODEL FIT INFORMATION | |
| Number of Free Parameters 45 | |
| Loglikelihood | |
| H0 Value -2531.783 | |
| H1 Value -2520.697 | |
| Information Criteria | |
| Akaike (AIC) 5153.567 | |
| Bayesian (BIC) 5270.800 | |
| Sample-Size Adjusted BIC 5128.678 | |
| (n* = (n + 2) / 24) | |
| Chi-Square Test of Model Fit | |
| Value 22.174 | |
| Degrees of Freedom 126 | |
| P-Value 1.0000 | |
| RMSEA (Root Mean Square Error Of Approximation) | |
| Estimate 0.000 | |
| 90 Percent C.I. 0.000 0.000 | |
| Probability RMSEA <= .05 1.000 | |
| CFI/TLI | |
| CFI 1.000 | |
| TLI 1.000 | |
| Chi-Square Test of Model Fit for the Baseline Model | |
| Value 48.695 | |
| Degrees of Freedom 153 | |
| P-Value 1.0000 | |
| SRMR (Standardized Root Mean Square Residual) | |
| Value 0.037 | |
| MODEL RESULTS | |
| Two-Tailed | |
| Estimate S.E. Est./S.E. P-Value | |
| C1 BY | |
| I1 1.000 0.000 999.000 999.000 | |
| I2 0.975 1.055 0.924 0.356 | |
| I3 1.490 1.417 1.052 0.293 | |
| C2 BY | |
| I4 1.000 0.000 999.000 999.000 | |
| I5 1.120 1.237 0.905 0.365 | |
| I6 2.488 3.932 0.633 0.527 | |
| C3 BY | |
| I7 1.000 0.000 999.000 999.000 | |
| I8 2.198 2.275 0.966 0.334 | |
| I9 1.199 1.233 0.972 0.331 | |
| C4 BY | |
| I10 1.000 0.000 999.000 999.000 | |
| I11 1.340 1.088 1.232 0.218 | |
| I12 1.010 0.770 1.312 0.190 | |
| C5 BY | |
| I13 1.000 0.000 999.000 999.000 | |
| I14 1.168 2.535 0.461 0.645 | |
| I15 4.236 7.169 0.591 0.555 | |
| C6 BY | |
| I16 1.000 0.000 999.000 999.000 | |
| I17 0.465 0.749 0.621 0.535 | |
| I18 0.669 1.028 0.651 0.515 | |
| C2 ON | |
| C1 0.237 0.465 0.510 0.610 | |
| C3 ON | |
| C1 -0.374 0.637 -0.588 0.556 | |
| C2 0.001 0.380 0.004 0.997 | |
| C4 ON | |
| C1 0.409 0.714 0.572 0.567 | |
| C3 -0.156 0.646 -0.241 0.809 | |
| C5 ON | |
| C1 0.344 0.687 0.501 0.616 | |
| C3 -0.181 0.429 -0.423 0.673 | |
| C6 ON | |
| C4 0.225 0.426 0.528 0.597 | |
| C6 WITH | |
| C5 0.013 0.029 0.461 0.645 | |
| Variances | |
| C1 0.053 0.081 0.658 0.510 | |
| Residual Variances | |
| I1 0.937 0.148 6.309 0.000 | |
| I2 0.939 0.148 6.351 0.000 | |
| I3 0.872 0.172 5.070 0.000 | |
| I4 0.944 0.155 6.080 0.000 | |
| I5 0.932 0.164 5.701 0.000 | |
| I6 0.705 0.466 1.512 0.131 | |
| I7 0.942 0.147 6.402 0.000 | |
| I8 0.758 0.253 3.001 0.003 | |
| I9 0.921 0.152 6.055 0.000 | |
| I10 0.870 0.164 5.298 0.000 | |
| I11 0.775 0.215 3.605 0.000 | |
| I12 0.868 0.165 5.253 0.000 | |
| I13 0.987 0.140 7.034 0.000 | |
| I14 0.985 0.141 7.002 0.000 | |
| I15 0.928 0.290 3.195 0.001 | |
| I16 0.832 0.283 2.936 0.003 | |
| I17 0.956 0.152 6.281 0.000 | |
| I18 0.919 0.178 5.168 0.000 | |
| C2 0.043 0.083 0.521 0.603 | |
| C3 0.041 0.066 0.616 0.538 | |
| C4 0.107 0.116 0.921 0.357 | |
| C5 -0.007 0.027 -0.254 0.800 | |
| C6 0.152 0.263 0.576 0.565 | |
| STANDARDIZED MODEL RESULTS | |
| STDYX Standardization | |
| Two-Tailed | |
| Estimate S.E. Est./S.E. P-Value | |
| C1 BY | |
| I1 0.232 0.174 1.333 0.182 | |
| I2 0.226 0.174 1.303 0.192 | |
| I3 0.346 0.196 1.763 0.078 | |
| C2 BY | |
| I4 0.216 0.209 1.035 0.301 | |
| I5 0.242 0.223 1.084 0.278 | |
| I6 0.537 0.434 1.237 0.216 | |
| C3 BY | |
| I7 0.220 0.172 1.282 0.200 | |
| I8 0.484 0.250 1.934 0.053 | |
| I9 0.264 0.177 1.496 0.135 | |
| C4 BY | |
| I10 0.348 0.181 1.923 0.054 | |
| I11 0.466 0.215 2.166 0.030 | |
| I12 0.351 0.182 1.933 0.053 | |
| C5 BY | |
| I13 0.059 0.158 0.372 0.710 | |
| I14 0.069 0.175 0.393 0.695 | |
| I15 0.249 0.533 0.468 0.640 | |
| C6 BY | |
| I16 0.399 0.337 1.185 0.236 | |
| I17 0.186 0.213 0.870 0.384 | |
| I18 0.267 0.248 1.078 0.281 | |
| C2 ON | |
| C1 0.255 0.339 0.751 0.453 | |
| C3 ON | |
| C1 -0.394 0.473 -0.833 0.405 | |
| C2 0.001 0.372 0.004 0.997 | |
| C4 ON | |
| C1 0.273 0.394 0.692 0.489 | |
| C3 -0.099 0.399 -0.247 0.805 | |
| C5 ON | |
| C1 1.356 3.014 0.450 0.653 | |
| C3 -0.679 1.765 -0.385 0.701 | |
| C6 ON | |
| C4 0.196 0.348 0.564 0.572 | |
| C6 WITH | |
| C5 999.000 999.000 999.000 999.000 | |
| Variances | |
| C1 1.000 0.000 999.000 999.000 | |
| Residual Variances | |
| I1 0.946 0.081 11.722 0.000 | |
| I2 0.949 0.078 12.091 0.000 | |
| I3 0.881 0.135 6.499 0.000 | |
| I4 0.953 0.090 10.593 0.000 | |
| I5 0.942 0.108 8.735 0.000 | |
| I6 0.712 0.466 1.527 0.127 | |
| I7 0.951 0.076 12.559 0.000 | |
| I8 0.765 0.243 3.156 0.002 | |
| I9 0.930 0.093 9.966 0.000 | |
| I10 0.879 0.126 6.989 0.000 | |
| I11 0.783 0.201 3.904 0.000 | |
| I12 0.877 0.128 6.872 0.000 | |
| I13 0.997 0.019 53.577 0.000 | |
| I14 0.995 0.024 41.402 0.000 | |
| I15 0.938 0.266 3.525 0.000 | |
| I16 0.841 0.269 3.125 0.002 | |
| I17 0.966 0.079 12.194 0.000 | |
| I18 0.929 0.132 7.019 0.000 | |
| C2 0.935 0.173 5.410 0.000 | |
| C3 0.845 0.345 2.449 0.014 | |
| C4 0.895 0.177 5.068 0.000 | |
| C5 -2.023 999.000 999.000 999.000 | |
| C6 0.962 0.136 7.052 0.000 | |
| R-SQUARE | |
| Observed Two-Tailed | |
| Variable Estimate S.E. Est./S.E. P-Value | |
| I1 0.054 0.081 0.667 0.505 | |
| I2 0.051 0.078 0.652 0.515 | |
| I3 0.119 0.135 0.882 0.378 | |
| I4 0.047 0.090 0.517 0.605 | |
| I5 0.058 0.108 0.542 0.588 | |
| I6 0.288 0.466 0.618 0.536 | |
| I7 0.049 0.076 0.641 0.522 | |
| I8 0.235 0.243 0.967 0.334 | |
| I9 0.070 0.093 0.748 0.455 | |
| I10 0.121 0.126 0.962 0.336 | |
| I11 0.217 0.201 1.083 0.279 | |
| I12 0.123 0.128 0.967 0.334 | |
| I13 0.003 0.019 0.186 0.852 | |
| I14 0.005 0.024 0.196 0.844 | |
| I15 0.062 0.266 0.234 0.815 | |
| I16 0.159 0.269 0.592 0.554 | |
| I17 0.034 0.079 0.435 0.664 | |
| I18 0.071 0.132 0.539 0.590 | |
| Latent Two-Tailed | |
| Variable Estimate S.E. Est./S.E. P-Value | |
| C2 0.065 0.173 0.376 0.707 | |
| C3 0.155 0.345 0.449 0.653 | |
| C4 0.105 0.177 0.596 0.551 | |
| C5 Undefined 0.30230E+01 | |
| C6 0.038 0.136 0.282 0.778 | |
| QUALITY OF NUMERICAL RESULTS | |
| Condition Number for the Information Matrix 0.256E-05 | |
| (ratio of smallest to largest eigenvalue) | |
| Beginning Time: 22:56:38 | |
| Ending Time: 22:56:38 | |
| Elapsed Time: 00:00:00 | |
| MUTHEN & MUTHEN | |
| 3463 Stoner Ave. | |
| Los Angeles, CA 90066 | |
| Tel: (310) 391-9971 | |
| Fax: (310) 391-8971 | |
| Web: www.StatModel.com | |
| Support: Support@StatModel.com | |
| Copyright (c) 1998-2011 Muthen & Muthen', file=tf) | |
| mplusResults <- readModels(target=tf) | |
| print(mplusResults$warnings) |
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